Choose your preferred view mode

Please select whether you prefer to view the MDPI pages with a view tailored for mobile displays or to view the MDPI
pages in the normal scrollable desktop version. This selection will be stored into your cookies and used automatically
in next visits. You can also change the view style at any point from the main header when using the pages with your
mobile device.

Topical Collection Information

Dear Colleagues,

The need to deliver electricity to customers: reliably, safely and cost effectively and in a sustainable manner, is always with us. To do this given the multiplicity of constraints means the electrical power system must be carefully engineered, not only to meet today's needs, but for the foreseeable future. The Smart Grid initiative is really about making the grid smarter than it is already (as in many cases the grid is already "smart") so as to achieve these objectives. Many countries are devoting time and resources to this initiative due to the immense potential benefits. The perceived benefits are:

Improved reliability and resilience

Better operational efficiency

Better utilization of resources

Better utilization of assets

Adequate Power Quality

The term Smart Grid means different things to different people as the perceived benefits, and hence drivers, are different in different countries. Regardless of one's concept of a Smart Grid, the need for a reliable two-way communication system is central. Because of the entwining of both the electrical power system and communication system to form a Smart Grid the two streams to this collection are Smart Grid communications and Smart Grid electrical power system.

Papers in the relevant area of Smart Grid communications, including but not limited to the following, are invited:

Manuscripts for the topical collection can be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on this website. The topical collection considers regular research articles, short communications and review articles. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page.

Australia has one of the highest rates of residential photovoltaics penetration in the world. The willingness of households to privately invest in energy infrastructure, and the maturing of battery technology, provides significant scope for more efficient energy networks. The purpose of this paper

Australia has one of the highest rates of residential photovoltaics penetration in the world. The willingness of households to privately invest in energy infrastructure, and the maturing of battery technology, provides significant scope for more efficient energy networks. The purpose of this paper is to evaluate the scope for promoting distributed generation and storage from within existing network spending. In this paper, a techno-economic analysis is conducted to evaluate the economic impacts on networks of private investment in energy infrastructure. A highly granular probabilistic model of households within a test area was developed and an economic evaluation of both household and network sectors performed. Results of this paper show that PV only installations carry the greatest private return and, at current battery prices, the economics of combined PV and battery systems is marginal. However, when network benefits arising from reducing residential evening peaks, improved reliability, and losses avoided are considered, this can more than compensate for private economic losses. The main conclusion of this paper is that there is significant scope for network benefits in retrofitting existing housing stock through the incentivization of a policy of a more rapid adoption of distributed generation and residential battery storage.
Full article

This paper introduces a distributed secondary control algorithm for automatic generation control (AGC) and automatic voltage control (AVC), which aims at matching area generation to area load and minimizing the total generation cost in an alternating current (AC) microgrids. Firstly, the control algorithm

This paper introduces a distributed secondary control algorithm for automatic generation control (AGC) and automatic voltage control (AVC), which aims at matching area generation to area load and minimizing the total generation cost in an alternating current (AC) microgrids. Firstly, the control algorithm utilizes a continuous-time distributed algorithm to generate additional control variables to achieve frequency-voltage recovery for all distributed generators (DGs). Secondary, it solves the economic dispatch problem (EDP) by a distributed economic incremental algorithm in the secondary control level, which avoids the problem caused by communication speed inconsistency between secondary and tertiary control levels. This study also utilizes a fully distributed strategy based on secondary communication network to estimate the total load demand. In addition, the proposed algorithm can be used to realize a seamless handover from the islanded mode to the grid-connected mode, run under the condition of short time communication system out of action, and help to realize the plug and play function. Lastly, the stability of the proposed control algorithm is analyzed and proved, and the effectiveness of the method is verified in some case studies.
Full article

The existing studies on probabilistic steady-state analysis of integrated energy systems (IES) are limited to integrated electricity and gas networks or integrated electricity and heating networks. This paper proposes a probabilistic steady-state analysis of integrated electricity, gas and heating networks (EGH-IES). Four typical operation modes of an EGH-IES are presented at first. The probabilistic energy flow problem of the EGS-IES considering its operation modes and correlated uncertainties in wind/solar power and electricity/gas/heat loads is then formulated and solved by the Monte Carlo method based on Latin hypercube sampling and Nataf transformation. Numerical simulations are conducted on a sample EGH-IES working in the “electricity/gas following heat” mode to verify the probabilistic analysis proposed in this paper and to study the effects of uncertainties and correlations on the operation of the EGH-IES, especially uncertainty transmissions among the subnetworks.
Full article

The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the

The state of transformer equipment is usually manifested through a variety of information. The characteristic information will change with different types of equipment defects/faults, location, severity, and other factors. For transformer operating state prediction and fault warning, the key influencing factors of the transformer panorama information are analyzed. The degree of relative deterioration is used to characterize the deterioration of the transformer state. The membership relationship between the relative deterioration degree of each indicator and the transformer state is obtained through fuzzy processing. Through the long short-term memory (LSTM) network, the evolution of the transformer status is extracted, and a data-driven state prediction model is constructed to realize preliminary warning of a potential fault of the equipment. Through the LSTM network, the quantitative index and qualitative index are organically combined in order to perceive the corresponding relationship between the characteristic parameters and the operating state of the transformer. The results of different time-scale prediction cases show that the proposed method can effectively predict the operation status of power transformers and accurately reflect their status.
Full article

Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and

Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and the operator. In this system, a priori knowledge about the energy load pattern can help reshape the load and cut the energy demand curve, thus allowing a better management and distribution of the energy in smart grid energy systems. Designing a computationally intelligent load forecasting (ILF) system is often a primary goal of energy demand management. This study explores the state of the art of computationally intelligent (i.e., machine learning) methods that are applied in load forecasting in terms of their classification and evaluation for sustainable operation of the overall energy management system. More than 50 research papers related to the subject identified in existing literature are classified into two categories: namely the single and the hybrid computational intelligence (CI)-based load forecasting technique. The advantages and disadvantages of each individual techniques also discussed to encapsulate them into the perspective into the energy management research. The identified methods have been further investigated by a qualitative analysis based on the accuracy of the prediction, which confirms the dominance of hybrid forecasting methods, which are often applied as metaheurstic algorithms considering the different optimization techniques over single model approaches. Based on extensive surveys, the review paper predicts a continuous future expansion of such literature on different CI approaches and their optimizations with both heuristic and metaheuristic methods used for energy load forecasting and their potential utilization in real-time smart energy management grids to address future challenges in energy demand management.
Full article

Nowadays, the incorporation and constant evolution of communication networks in the electricity sector have given rise to the so-called Smart Grid, which is why it is necessary to have devices that are capable of managing new communication protocols, guaranteeing the strict requirements of

Nowadays, the incorporation and constant evolution of communication networks in the electricity sector have given rise to the so-called Smart Grid, which is why it is necessary to have devices that are capable of managing new communication protocols, guaranteeing the strict requirements of processing required by the electricity sector. In this context, intelligent electronic devices (IEDs) with network architectures are currently available to meet the communication, real-time processing and interoperability requirements of the Smart Grid. The new generation IEDs include an Field Programmable Gate Array (FPGA), to support specialized networking switching architectures for the electric sector, as the IEEE 1588-aware High-availability Seamless Redundancy/Parallel Redundancy Protocol (HSR/PRP). Another advantage to using an FPGA is the ability to update or reconfigure the design to support new requirements that are being raised to the standards (IEC 61850). The update of the architecture implemented in the FPGA can be done remotely, but it is necessary to establish a cyber security mechanism since the communication link generates vulnerability in the case the attacker gains physical access to the network. The research presented in this paper proposes a secure protocol and Intellectual Property (IP) core for configuring and monitoring the networking IPs implemented in a Field Programmable Gate Array (FPGA). The FPGA based implementation proposed overcomes this issue using a light Layer-2 protocol fully implemented on hardware and protected by strong cryptographic algorithms (AES-GCM), defined in the IEC 61850-90-5 standard. The proposed secure protocol and IP core are applicable in any field where remote configuration over Ethernet is required for IP cores in FPGAs. In this paper, the proposal is validated in communications hardware for Smart Grids.
Full article

The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The

The paper introduces a definition of dual graph grammar. It enables two graphs to share information in a synchronized way. A smart city example application, which is an outdoor lighting control system utilizing the dual graph grammar, is also demonstrated. The system controls dimming of street lights which is based on traffic intensity. Each luminaire’s light level is adjusted individually to comply with the lighting norms to ensure safety. Benefits of applying the dual graph grammar are twofold. First, it increases expressive power of the mathematical model that the system uses. It becomes possible to take into account complex geographical distribution of sensors and logical dependencies among them. Second, it increases the system’s efficiency by reducing the problem size during run-time. Experimental results show a reduction of the computation time by a factor of 2.8. The approach has been verified in practice.
Full article

Currently, Advanced Metering Infrastructure (AMI) systems have equipped the low voltage section with a communication system that is being used mainly for metering purposes, but it can be further employed for additional applications related to the Smart Grid (SG) concept. This paper explores

Currently, Advanced Metering Infrastructure (AMI) systems have equipped the low voltage section with a communication system that is being used mainly for metering purposes, but it can be further employed for additional applications related to the Smart Grid (SG) concept. This paper explores the potential applications beyond metering of the available channel in a Power Line Communication-based AMI system. To that end, IP has been implemented over Narrow Band-Power Line Communication (NB-PLC) in a real microgrid, which includes an AMI system. A thorough review of potential applications for the SG that might be implemented for this representative case is included in order to provide a realistic analysis of the potentiality of NB-PLC beyond smart metering. The results demonstrate that existing AMI systems based on NB-PLC have the capacity to implement additional applications such as remote commands or status signals, which entails an added value for deployed AMI systems.
Full article

Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP) can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of

Demand response is nowadays considered as another type of generator, beyond just a simple peak reduction mechanism. A demand response service provider (DRSP) can, through its subcontracts with many energy customers, virtually generate electricity with actual load reduction. However, in this type of virtual generator, the amount of load reduction includes inevitable uncertainty, because it consists of a very large number of independent energy customers. While they may reduce energy today, they might not tomorrow. In this circumstance, a DSRP must choose a proper set of these uncertain customers to achieve the exact preferred amount of load curtailment. In this paper, the customer selection problem for a service provider that consists of uncertain responses of customers is defined and solved. The uncertainty of energy reduction is fully considered in the formulation with data-driven probability distribution modeling and stochastic programming technique. The proposed optimization method that utilizes only the observed load data provides a realistic and applicable solution to a demand response system. The performance of the proposed optimization is verified with real demand response event data in Korea, and the results show increased and stabilized performance from the service provider’s perspective.
Full article

Almost one third of the energy is used in the residential sector, and space heating is the largest part of energy consumption in our houses. Knowledge about the thermal characteristics of a house can increase the awareness of homeowners about the options to

Almost one third of the energy is used in the residential sector, and space heating is the largest part of energy consumption in our houses. Knowledge about the thermal characteristics of a house can increase the awareness of homeowners about the options to save energy, for example by showing that there is room for improvement of the insulation level. However, calculating the exact value of these characteristics is not possible without precise thermal experiments. In this paper, we propose a method to automatically estimate two of the most important thermal characteristics of a house, i.e., the loss rate and the heat capacity, based on collected data about the temperature and gas usage. The method is evaluated with a data set that has been collected in a real-life case study. Although a ground truth is lacking, the analyses show that there is evidence that this method could provide a feasible way to estimate those values from the thermostat data. More detailed data about the houses in which the data was collected is required to draw stronger conclusions. We conclude that the proposed method is a promising way to add energy saving advice to smart thermostats.
Full article

With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading

With the rapid growth of usage of phasor measurement units (PMUs) for modern power grids, the application of synchronized phasors (synchrophasors) to real-time voltage security monitoring has become an active research area. This paper presents a novel approach for fast determination of loading margin using PMU data from a wide-area monitoring system (WAMS) to construct the voltage stability boundary (VSB) of a transmission grid. Specifically, a new approach for online loading margin estimation that considers system load trends is proposed based on the Thevenin equivalent (TE) technique and the Mobius transformation (MT) technique. A VSB is then computed by means of real-time PMU measurements and is presented in a complex load power space. VSB can be utilized as a visualization tool that is able to provide real-time visualization of the current voltage stability situation. The proposed method is fast and adequate for online voltage security assessment. Furthermore, it enables us to significantly increase a system operator’s situational awareness for operational decision making. Simulation studies were carried out using different sized power grid models under various operating conditions. The simulation results are shown to validate the capability of the proposed method.
Full article

Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing

Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation.
Full article

Most power line communication (PLC) models are designed to date simulate power lines as two-wire lines. However, in alternating current (AC) electrical distribution, the two-wire option is seldom applied, and medium-voltage lines are most often based on the three-phase configuration. In this context,

Most power line communication (PLC) models are designed to date simulate power lines as two-wire lines. However, in alternating current (AC) electrical distribution, the two-wire option is seldom applied, and medium-voltage lines are most often based on the three-phase configuration. In this context, the influence of the ground, which constitutes another conductor with specific parameters, cannot be neglected. Two-wire models are characterized by limited accuracy, not allowing us to simulate certain major phenomena affecting PLC. This, for example, could embody the answer to the question of whether it is more advantageous to transmit a signal independently through each phase, reference the signal with respect to another phase or to use the ground as a reference. This paper discusses a multi-conductor model that eliminates the disadvantages outlined above; the proposed model exploits the multi-conductor telegrapher’s equations. In order to be able to include medium-voltage (MV)/ low-voltage (LV) transformers in medium-voltage network models, we constituted a transformer model. The designed models were validated on a real medium-voltage network. To be able to evaluate the suitability of the PLC, the noise in the medium voltage network was measured in order to determine the signal-to-noise ratio (SNR).
Full article

The phase-shifted full-bridge (PSFB) converter is widely employed in high-power applications. However, circulating current, duty-cycle loss, secondary voltage oscillation, and narrow zero-voltage-switching (ZVS) range are the main drawbacks of the conventional PSFB converter. This paper proposes a novel full-bridge converter to improve the

The phase-shifted full-bridge (PSFB) converter is widely employed in high-power applications. However, circulating current, duty-cycle loss, secondary voltage oscillation, and narrow zero-voltage-switching (ZVS) range are the main drawbacks of the conventional PSFB converter. This paper proposes a novel full-bridge converter to improve the performance of the conventional PSFB converter. The proposed converter contains two paralleled half-bridge inverters and an auxiliary inductor on the primary side. The rectifier stage is composed of six diodes connected with the form of full-bridge rectification. This structure allows the stored energy for ZVS operation to change adaptively with duty-cycle. The power can be transferred from the primary side to the secondary side during the whole period. Therefore, the requirement of output filter inductance is reduced and the circulating current is removed. The proposed converter is a good candidate for high power, high voltage and variable input voltage applications. The operation principle and performance are verified on a laboratory prototype.
Full article

The penetration of various types of renewable sources and on-site storage devices have recently focused attention towards DC power distribution in consumer grids to achieve the target of zero/positive energy buildings and communities. To achieve this target, the most important component is the

The penetration of various types of renewable sources and on-site storage devices have recently focused attention towards DC power distribution in consumer grids to achieve the target of zero/positive energy buildings and communities. To achieve this target, the most important component is the DC consumer grid architecture which can integrate not only renewable sources and storage, but also enable the implementation in any conventional AC distribution network without any significant upgrade. To this end, a unique DC Transformer enabled DC microgrid architecture is presented in this paper. The architecture, called PCmRC (power controlling monitoring routing center) is proposed to manage distributed energy sources and storage at any stage and also directly interconnects the DC consumer grid with the conventional AC power grid. This paper also investigates detailed control algorithms of each component and the DC Transformer topology in addition to proposing four unique stages of grid operational modes to enhance the overall grid stability in any operational condition. The main objectives are to maximize the exploitation of renewable sources, to decrease reliance on fossil fuels, to boost the overall efficiency of the grid by reducing the power conversion losses and demand side management in all possible forms. The simulation platform is designed in MATLAB/Simulink. Simulation results of several types of case studies show the effectiveness of the proposed power distribution and management model.
Full article

As power systems develop rapidly into smarter and more flexible configurations, so too must the communication technologies that support them. Machine-to-machine (M2M) communication in power systems enables information collection by combining sensors and communication protocols. In doing so, M2M technology supports communication between

As power systems develop rapidly into smarter and more flexible configurations, so too must the communication technologies that support them. Machine-to-machine (M2M) communication in power systems enables information collection by combining sensors and communication protocols. In doing so, M2M technology supports communication between machines to improve power quality and protection coordination. When functioning in a “smart grid” environment, M2M has been labelled by the European Telecommunications Standard Institute (ETSI). International Electronical Committee (IEC) 61850 as the most important standard in power network systems. As evidence, this communication platform has been used for device data collection/control in substation automation systems and distribution automation systems. If the IEC 61850 information model were to be combined with a set of contemporary web protocols, the potential benefits would be enormous. Therefore, a constrained application protocol (CoAP) has been adopted to create an ETSI M2M communication architecture. CoAP is compared with other protocols (MQTT, SOAP) to demonstrate the validity of using it. This M2M communication technology is applied in an IEC61850, and use the OPNET Modeler 17.1 to demonstrate intercompatibility of CoAP Gateway. The proposed IEC 61850 and CoAP mapping scheme reduces the mapping time and improves throughput. CoAP is useful in the ETSI M2M environment where device capability is able to be limited.
Full article

The electronic power transformer (EPT) raises concerns for its notable size and volume reduction compared with traditional line frequency transformers. Medium frequency transformers (MFTs) are important components in high voltage and high power energy conversion systems such as EPTs. High voltage and high

The electronic power transformer (EPT) raises concerns for its notable size and volume reduction compared with traditional line frequency transformers. Medium frequency transformers (MFTs) are important components in high voltage and high power energy conversion systems such as EPTs. High voltage and high power make the reliable insulation design of MFT more difficult. In this paper, the influence of wire type and interleaved winding structure on the electric field distribution of MFT is discussed in detail. The electric field distributions for six kinds of typical non-interleaved windings with different wire types are researched using a 2-D finite element method (FEM). The electric field distributions for one non-interleaved winding and two interleaved windings are also studied using 2-D FEM. Furthermore, the maximum electric field intensities are obtained and compared. The results show that, in this case study, compared with foil conductor, smaller maximum electric field intensity can be achieved using litz wire in secondary winding. Besides, interleaving can increase the maximum electric field intensity when insulation distance is constant. The proposed method of studying the electric field distribution and analysis results are expected to make a contribution to the improvement of electric field distribution in transformers.
Full article

In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC) transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR) is proposed in this paper. The VSWR is defined considering a

In order to improve the fault monitoring performance of grounding electrode lines in ultra-high voltage DC (UHVDC) transmission systems, a novel fault monitoring approach based on the high-frequency voltage standing-wave ratio (VSWR) is proposed in this paper. The VSWR is defined considering a lossless transmission line, and the characteristics of the VSWR under different conditions are analyzed. It is shown that the VSWR equals 1 when the terminal resistance completely matches the characteristic impedance of the line, and when a short circuit fault occurs on the grounding electrode line, the VSWR will be greater than 1. The VSWR will approach positive infinity under metallic earth fault conditions, whereas the VSWR in non-metallic earth faults will be smaller. Based on these analytical results, a fault supervision criterion is formulated. The effectiveness of the proposed VSWR-based fault supervision technique is verified with a typical UHVDC project established in Power Systems Computer Aided Design/Electromagnetic Transients including DC(PSCAD/EMTDC). Simulation results indicate that the proposed strategy can reliably identify the grounding electrode line fault and has strong anti-fault resistance capability.
Full article

In this paper, we propose a dynamic economic dispatch (DED) model with sharing of responsibility for supply–demand balance under uncertain demands in a microgrid (MG). For developing the proposed model, an energy band operation scheme, including a tie-line flow (TLF) contraction between the

In this paper, we propose a dynamic economic dispatch (DED) model with sharing of responsibility for supply–demand balance under uncertain demands in a microgrid (MG). For developing the proposed model, an energy band operation scheme, including a tie-line flow (TLF) contraction between the main grid and the microgrid (MG), is constructed for preventing considerable changes in the TLFs caused by DED optimization. The proposed scheme generalizes the relationship between TLF contractions and MG operational costs. Moreover, a chance-constrained approach is applied to prevent short- and over-supply risks caused by unpredictable demands in the MG. Based on this approach, it is possible to determine the reasonable ramping capability versus operational cost under uncertain power demands in the MG.
Full article

This paper presents an optimal cooperative voltage control approach, which coordinates storage units in a distribution network. This technique is developed for storage systems’ active power management with a local strategy to provide robust voltage control and a distributed strategy to deliver optimal

This paper presents an optimal cooperative voltage control approach, which coordinates storage units in a distribution network. This technique is developed for storage systems’ active power management with a local strategy to provide robust voltage control and a distributed strategy to deliver optimal storage utilization. Accordingly, three control criteria based on predefined node voltage limits are used for network operation including normal, over-voltage, and under-voltage control modes. The contribution of storage units for voltage support is determined using the control modes and the coordination strategies proposed in this paper. This technique is evaluated in two case studies to assess its capability.
Full article

Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper.
Full article

This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify

This paper describes and assesses a decentralized solution based on a wireless sensor-actuator network to provide primary frequency control from demand response in power systems with high wind energy penetration and, subsequently, with relevant frequency excursions. The proposed system is able to modify the electrical power demand of a variety of thermostatically-controlled loads, maintaining minimum comfort levels and minimizing both infrastructure requirements and primary reserves from the supply side. This low-cost hardware solution avoids any additional wiring, extending the wireless sensor-actuator network technology towards small customers, which account for over a 30% share of the current power demand. Frequency excursions are collected by each individual load controller, considering not only the magnitude of the frequency deviation, but also their evolution over time. Based on these time-frequency excursion characteristics, controllers are capable of modifying the power consumption of thermostatically-controlled loads by switching them off and on, thus contributing to primary frequency control in power systems with higher generation unit oscillations as a consequence of relevant wind power integration. Field tests have been carried out in a laboratory environment to assess the load controller performance, as well as to evaluate the electrical and thermal response of individual loads under frequency deviations. These frequency deviations are estimated from power systems with a high penetration of wind energy, which are more sensitive to frequency oscillations and where demand response can significantly contribute to mitigate these frequency excursions. The results, also included in the paper, evaluate the suitability of the proposed load controllers and their suitability to decrease frequency excursions from the demand side in a decentralized manner.
Full article

The three-phase three-wire neutral-point-clamped shunt active power filter (NPC-SAPF), which most adopts classical closed-loop feedback control methods such as proportional-integral (PI), proportional-resonant (PR) and repetitive control, can only output 1st–25th harmonic currents with 10–20 kHz switching frequency. The reason for this is that

The three-phase three-wire neutral-point-clamped shunt active power filter (NPC-SAPF), which most adopts classical closed-loop feedback control methods such as proportional-integral (PI), proportional-resonant (PR) and repetitive control, can only output 1st–25th harmonic currents with 10–20 kHz switching frequency. The reason for this is that the controller design must make a compromise between system stability and harmonic current compensation ability under the condition of less than 20 kHz switching frequency. To broaden the bandwidth of the compensation current, a Lyapunov stability theory-based control strategy is presented in this paper for NPC-SAPF. The proposed control law is obtained by constructing the switching function on the basis of the mathematical model and the Lyapunov candidate function, which can avoid introducing closed-loop feedback control and keep the system globally asymptotically stable. By means of the proposed method, the NPC-SAPF has compensation ability for the 1st–50th harmonic currents, the total harmonic distortion (THD) and each harmonic content of grid currents satisfy the requirements of IEEE Standard 519-2014. In order to verify the superiority of the proposed control strategy, stability conditions of the proposed strategy and the representative PR controllers are compared. The simulation results in MATLAB/Simulink (MathWorks, Natick, MA, USA) and the experimental results obtained on a 6.6 kVA NPC-SAPF laboratory prototype validate the proposed control strategy.
Full article

This paper proposes a novel energy based technique called the Robustness Area (RA) technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs). The motivation is on account of the latest blackouts in Brazil, where the local

This paper proposes a novel energy based technique called the Robustness Area (RA) technique that measures power system robustness levels, as a helper for planning Power System Restorations (PSRs). The motivation is on account of the latest blackouts in Brazil, where the local Independent System Operator (ISO) encountered difficulties related to circuit disconnections during the restoration. The technique identifies vulnerable and robust buses, pointing out system areas that should be firstly reinforced during PSR, in order to enhance system stability. A Brazilian power system restoration area is used to compare the guidelines adopted by the ISO with a more suitable new plan indicated by the RA tool. Active power and reactive power load margin and standing phase angle show the method efficiency as a result of a well balanced system configuration, enhancing the restoration performance. Time domain simulations for loop closures and severe events also show the positive impact that the proposed tool brings to PSRs.
Full article

There are difficulties in analyzing the stability of microgrids since they are located on various network structures. However, considering that the network often consists of passive elements, the passivity theory is applied in this paper to solve the above-mentioned problem. It has been

There are difficulties in analyzing the stability of microgrids since they are located on various network structures. However, considering that the network often consists of passive elements, the passivity theory is applied in this paper to solve the above-mentioned problem. It has been formerly shown that when the network is weakly strictly positive real (WSPR), the DC microgrid is stable if all interfaces between the microgrid and converters are made to be passive, which is called interface passivity. Then, the feedback passivation method is proposed for the controller design of various DC–DC converters to achieve the interface passivity. The interface passivity is different from the passivity of closed-loop systems on which the passivity based control (PBC) concentrates. The feedback passivation design is detailed for typical buck converters and boost converters in terms of conditions that the controller parameters should satisfy. The theoretical results are verified by a hardware-in-loop real-time labotray (RTLab) simulation of a DC microgrid with four generators.
Full article

A direct deadbeat voltage control design method for inverter-based microgrid applications is proposed in this paper. When the inductor-capacitor (LC) filter output voltage is directly controlled using voltage source inverters (VSIs), the plant dynamics exhibit second-order resonant characteristics with a load current disturbance.

A direct deadbeat voltage control design method for inverter-based microgrid applications is proposed in this paper. When the inductor-capacitor (LC) filter output voltage is directly controlled using voltage source inverters (VSIs), the plant dynamics exhibit second-order resonant characteristics with a load current disturbance. To effectively damp the resonance caused by the output LC filter, an active damping strategy that does not cause additional energy loss is utilized. The proposed direct deadbeat voltage control law is devised from a detailed, actively damped LC plant model. The proposed deadbeat control method enhances voltage control performance owing to its better disturbance rejection capability than the conventional deadbeat or proportional-integral-based control methods. The most important advantage of the proposed deadbeat control method is that it makes the deadbeat control more robust by bringing discrete closed-loop poles closer to the origin. Simulation and experimental results are shown to verify the enhanced voltage control performance and stability of the proposed voltage control method.
Full article

The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of

The paper develops a multi-objective planning framework for distribution network expansion with electric vehicle charging stations. Charging loads are modeled in the first place, and then integrated into the optimal distribution network expansion planning. The formulation is extended from the single objective of the economic cost minimization into three objectives with the additional maximization of the charging station utilization, and maximization of the reliability level. Compared with the existing models, it captures the interactive impacts between charging infrastructures planning and distribution network planning from the aspects of economy, utilization, and reliability. A multi-stage search strategy is designed to solve the multi-objective problem. The models and the strategy are demonstrated by the test case. The results show that the proposed planning framework can make a trade-off among the three objectives, and offer a perspective to effectively integrate the network constraints from both the transportation network and distribution network.
Full article

In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization

In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance of these methods with the use of multi-dimensional signaling is also compared with this technique, which has previously been shown to boost metaheuristics performance for single-objective problems. Hence, multi-dimensional signaling is adapted and implemented here for the proposed multi-objective problem. In addition, parallel computing is used to mitigate the methods’ computational execution time. To validate the proposed techniques, a realistic case study for a chosen area of the northern region of Portugal is considered, namely part of Vila Real distribution grid (233-bus). It is assumed that this grid is managed by an energy aggregator entity, with reasonable amount of electric vehicles (EVs), several distributed generation (DG), customers with demand response (DR) contracts and energy storage systems (ESS). The considered case study characteristics took into account several reported research works with projections for 2020 and 2050. The findings strongly suggest that the signaling method clearly improves the results and the Pareto front region quality.
Full article

Machine learning techniques have been widely used in transient stability prediction of power systems. When using the post-fault dynamic responses, it is difficult to draw a definite conclusion about how long the duration of response data used should be in order to balance

Machine learning techniques have been widely used in transient stability prediction of power systems. When using the post-fault dynamic responses, it is difficult to draw a definite conclusion about how long the duration of response data used should be in order to balance the accuracy and speed. Besides, previous studies have the problem of lacking consideration for the confidence level. To solve these problems, a hierarchical method for transient stability prediction based on the confidence of ensemble classifier using multiple support vector machines (SVMs) is proposed. Firstly, multiple datasets are generated by bootstrap sampling, then features are randomly picked up to compress the datasets. Secondly, the confidence indices are defined and multiple SVMs are built based on these generated datasets. By synthesizing the probabilistic outputs of multiple SVMs, the prediction results and confidence of the ensemble classifier will be obtained. Finally, different ensemble classifiers with different response times are built to construct different layers of the proposed hierarchical scheme. The simulation results show that the proposed hierarchical method can balance the accuracy and rapidity of the transient stability prediction. Moreover, the hierarchical method can reduce the misjudgments of unstable instances and cooperate with the time domain simulation to insure the security and stability of power systems.
Full article

Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power

Recently, microgrids are attracting increasing research interest as promising technologies to integrate renewable energy resources into the distribution system. Although many works have been done on droop control applied to microgrids, they mainly focus on achieving proportional power sharing based on the power rating of the power converters. With various primary source for the distributed generator (DG), factors that are closely related to the operation cost, such as fuel cost of the generators and losses should be taken into account in order to improve the efficiency of the whole system. In this paper, a multiagent-based distributed method is proposed to minimize the operation cost in AC microgrids. In the microgrid, each DG is acting as an agent which regulates the power individually using a novel power regulation method based on frequency scheduling. An optimal power command is obtained through carefully designed consensus algorithm by using sparse communication links only among neighbouring agents. Experimental results for different cases verified that the proposed control strategy can effectively reduce the operation cost.
Full article

In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers.

In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers. Therefore, an unexpected under-voltage violation can occur due to the variation of active power output from the intermittent DGs. In order to prevent the under-voltage violation and improve the CVR effect, a new reactive power controller which complies with the IEEE Std. 1547TM, and a parameter determination method for the controller are proposed. In addition, an optimal power flow (OPF) problem to determine references for the resources of CVR is formulated with consideration of the intermittent DGs. The proposed method is validated using a modified IEEE 123-node test feeder. With the proposed method, the voltages of the test system are maintained to be greater than the lower bound, even though the active power outputs of the DGs are varied. Moreover, the CVR effect is improved compared to that used with the conventional reactive power control methods.
Full article

In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution

In the last few years, due to the technological improvement of advanced metering infrastructures, water and natural gas grids can be regarded as smart-grids, similarly to power ones. However, considering the number of studies related to the application of computational intelligence to distribution grids, the gap between power grids and water/gas grids is notably wide. For this purpose, in this paper, a framework for leakage identification is presented. The framework is composed of three sections aimed at the extraction and the selection of features and at the detection of leakages. A variation of the Sequential Feature Selection (SFS) algorithm is used to select the best performing features within a set, including, also, innovative temporal ones. The leakage identification is based on novelty detection and exploits the characterization of a normality model. Three statistical approaches, The Gaussian Mixture Model (GMM), Hidden Markov Model (HMM) and One-Class Support Vector Machine (OC-SVM), are adopted, under a comparative perspective. Both residential and office building environments are investigated by means of two datasets. One is the Almanac of Minutely Power dataset (AMPds), and it provides water and gas data consumption at 1, 10 and 30 min of time resolution; the other is the Department of International Development (DFID) dataset, and it provides water and gas data consumption at 30 min of time resolution. The achieved performance, computed by means of the Area Under the Curve (AUC), reaches 90% in the office building case study, thus confirming the suitability of the proposed approach for applications in smart water and gas grids.
Full article

In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on

In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on more challenging scenarios in which jobs are non-interruptible and non-power-shiftable. In addition, as more and more newly-built homes have rooftop solar arrays, it is assumed that all users are equipped with a solar-plus-battery system in this paper. Thus, power can be drawn from the battery as needed to reduce the cost of electricity or to lower the overall system load. With a quadratic load-dependent cost function, this paper first shows that the electricity cost minimization problem in such a setting is NP-hard and presents a distributed demand-side management algorithm, called DDSM, to solve this. Experimental results show that the proposed DDSM algorithm is effective, scalable and converges to a Nash equilibrium in finite rounds.
Full article

Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed

Advanced metering infrastructure (AMI) subsystems monitor and control energy distribution through exchange of information between smart meters and utility networks. A key challenge is how to select a cost-effective communication system without compromising the performance of the applications. Current communication technologies were developed for conventional data networks with different requirements. It is therefore necessary to investigate how much of existing communication technologies can be retrofitted into the new energy infrastructure to cost-effectively deliver acceptable level of service. This paper investigates broadband power line communications (BPLC) as a backhaul solution in AMI. By applying the disparate traffic characteristics of selected AMI applications, the network performance is evaluated. This study also examines the communication network response to changes in application configurations in terms of packet sizes. In each case, the network is stress-tested and performance is assessed against acceptable thresholds documented in the literature. Results show that, like every other communication technology, BPLC has certain limitations; however, with some modifications in the network topology, it indeed can fulfill most AMI traffic requirements for flexible and time-bounded applications. These opportunities, if tapped, can significantly improve fiscal and operational efficiencies in AMI services. Simulation results also reveal that BPLC as a backhaul can support flat and clustered AMI structures with cluster size ranging from 1 to 150 smart meters.
Full article

On remote islands photovoltaic (PV) panels with battery energy storage systems (BESSs) supply electric power to customers in parallel operation with engine generators (EGs) to reduce fuel consumption and environmental burden. A BESS operates in voltage control mode when it supplies power to

On remote islands photovoltaic (PV) panels with battery energy storage systems (BESSs) supply electric power to customers in parallel operation with engine generators (EGs) to reduce fuel consumption and environmental burden. A BESS operates in voltage control mode when it supplies power to loads alone, while it operates in current control mode when it supplies power to loads in parallel with the EG. This paper proposes a smooth mode change of the BESS from current control to voltage control by using initial value at the output of integral part in the voltage controller, and a smooth mode change from voltage control to current control by tracking the EG output voltage to the BESS output voltage using a phase-locked loop (PLL). The feasibility of the proposed scheme was verified through computer simulations and experiments with a scaled prototype.
Full article

The integration of renewable power sources with power grids presents many challenges, such as synchronization with the grid, power quality problems and so on. The shunt active power filter (SAPF) can be a solution to address the issue while suppressing the grid-end current

The integration of renewable power sources with power grids presents many challenges, such as synchronization with the grid, power quality problems and so on. The shunt active power filter (SAPF) can be a solution to address the issue while suppressing the grid-end current harmonics and distortions. Nonetheless, available SAPFs work somewhat unpredictably in practice. This is attributed to the dependency of the SAPF controller on nonlinear complicated equations and two distorted variables, such as load current and voltage, to produce the current reference. This condition will worsen when the plant includes wind turbines which inherently produce 3rd, 5th, 7th and 11th voltage harmonics. Moreover, the inability of the typical phase locked loop (PLL) used to synchronize the SAPF reference with the power grid also disrupts SAPF operation. This paper proposes an improved synchronous reference frame (SRF) which is equipped with a wavelet-based PLL to control the SAPF, using one variable such as load current. Firstly the fundamental positive sequence of the source voltage, obtained using a wavelet, is used as the input signal of the PLL through an orthogonal signal generator process. Then, the generated orthogonal signals are applied through the SRF-based compensation algorithm to synchronize the SAPF’s reference with power grid. To further force the remained uncompensated grid current harmonics to pass through the SAPF, an improved series filter (SF) equipped with a current harmonic suppression loop is proposed. Concurrent operation of the improved SAPF and SF is coordinated through a unified power quality conditioner (UPQC). The DC-link capacitor of the proposed UPQC, used to interconnect a photovoltaic (PV) system to the power grid, is regulated by an adaptive controller. Matlab/Simulink results confirm that the proposed wavelet-based UPQC results in purely sinusoidal grid-end currents with total harmonic distortion (THD) = 1.29%, which leads to high electrical efficiency of a grid-connected PV system.
Full article

High availability is crucial for industrial Ethernet networks as well as Ethernet-based control systems such as automation networks and substation automation systems (SAS). Since standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using

High availability is crucial for industrial Ethernet networks as well as Ethernet-based control systems such as automation networks and substation automation systems (SAS). Since standard Ethernet does not support fault tolerance capability, the high availability of Ethernet networks can be increased by using redundancy protocols. Various redundancy protocols for Ethernet networks have been developed and standardized, such as rapid spanning tree protocol (RSTP), media redundancy protocol (MRP), parallel redundancy protocol (PRP), high-availability seamless redundancy (HSR) and others. RSTP and MRP have switchover delay drawbacks. PRP provides zero recovery time, but requires a duplicate network infrastructure. HSR operation is similar to PRP, but HSR uses a single network. However, the standard HSR protocol is mainly applied to ring-based topologies and generates excessively unnecessary redundant traffic in the network. In this paper, we develop a new switching node for the HSR protocol, called SwitchBox, which is used in HSR networks in order to support any network topology and significantly reduce redundant network traffic, including unicast, multicast and broadcast traffic, compared with standard HSR. By using the SwitchBox, HSR not only provides seamless communications with zero switchover time in case of failure, but it is also easily applied to any network topology and significantly reduces unnecessary redundant traffic in HSR networks.
Full article

The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is

The clustering of electricity customers might have an effective meaning if, and only if, it is verified by domain experts. Most of the previous studies on customer clustering, however, do not consider real applications, but only the structure of clusters. Therefore, there is no guarantee that the clustering results are applicable to real domains. In other words, the results might not coincide with those of domain experts. In this paper, we focus on formulating clusters that are applicable to real applications based on domain expert knowledge. More specifically, we try to define a distance between customers that generates clusters that are applicable to demand response applications. First, the k-sliding distance, which is a new distance between two electricity customers, is proposed for customer clustering. The effect of k-sliding distance is verified by expert knowledge. Second, a genetic programming framework is proposed to automatically determine a more improved distance measure. The distance measure generated by our framework can be considered as a reflection of the clustering principles of domain experts. The results of the genetic programming demonstrate the possibility of deriving clustering principles.
Full article

This paper investigates several existing techniques for reducing high-availability seamless redundancy (HSR) unicast traffic in HSR networks for substation automation systems (SAS). HSR is a redundancy protocol for Ethernet networks that provides duplicate frames for separate physical paths with zero recovery time. This feature of HSR makes it very suited for real-time and mission-critical applications such as SAS systems. HSR is one of the redundancy protocols selected for SAS systems. However, the standard HSR protocol generates too much unnecessary redundant unicast traffic in connected-ring networks. This drawback degrades network performance and may cause congestion and delay. Several techniques have been proposed to reduce the redundant unicast traffic, resulting in the improvement of network performance in HSR networks. These HSR traffic reduction techniques are broadly classified into two categories based on their traffic reduction manner, including traffic filtering-based techniques and predefined path-based techniques. In this paper, we provide an overview and comparison of these HSR traffic reduction techniques found in the literature. The concepts, operational principles, network performance, advantages, and disadvantages of these techniques are investigated, summarized. We also provide a comparison of the traffic performance of these HSR traffic reduction techniques.
Full article

The smart grid (SG) is a promising platform for providing more reliable, efficient, and cost effective electricity to the consumers in a secure manner. Numerous initiatives across the globe are taken by both industry and academia in order to compile various security issues

The smart grid (SG) is a promising platform for providing more reliable, efficient, and cost effective electricity to the consumers in a secure manner. Numerous initiatives across the globe are taken by both industry and academia in order to compile various security issues in the smart grid network. Unfortunately, there is no impactful survey paper available in the literature on authentications in the smart grid network. Therefore, this paper addresses the required objectives of an authentication protocol in the smart grid network along with the focus on mutual authentication, access control, and secure integration among different SG components. We review the existing authentication protocols, and analyze mutual authentication, privacy, trust, integrity, and confidentiality of communicating information in the smart grid network. We review authentications between the communicated entities in the smart grid, such as smart appliance, smart meter, energy provider, control center (CC), and home/building/neighborhood area network gateways (GW). We also review the existing authentication schemes for the vehicle-to-grid (V2G) communication network along with various available secure integration and access control schemes. We also discuss the importance of the mutual authentication among SG entities while providing confidentiality and privacy preservation, seamless integration, and required access control with lower overhead, cost, and delay. This paper will help to provide a better understanding of current authentication, authorization, and secure integration issues in the smart grid network and directions to create interest among researchers to further explore these promising areas.
Full article

The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart

The evolution of the electricity grid towards the smart grid paradigm is fostering the integration of distributed renewable energy sources in smart buildings: a combination of local power generation, battery storage and controllable loads can greatly increase the energetic self-sufficiency of a smart building, enabling it to maximize the self-consumption of photovoltaic electricity and to participate in the energy market, thus taking advantage of time-variable tariffs to achieve economic savings. This paper proposes an energy management infrastructure specifically tailored for a smart office building, which relies on measured data and on forecasting algorithms to predict the future patterns of both local energy generation and power loads. The performance is compared to the optimal energy usage scheduling, which would be obtained assuming the exact knowledge of the future energy production and consumption trends, showing gaps below 10% with respect to the optimum.
Full article

Voltage is an important variable that reflects system conditions in DC distribution systems and affects many characteristics of a system. In a DC distribution system, there is a close relationship between the real power and the voltage magnitude, and this is one of

Voltage is an important variable that reflects system conditions in DC distribution systems and affects many characteristics of a system. In a DC distribution system, there is a close relationship between the real power and the voltage magnitude, and this is one of major differences from the characteristics of AC distribution systems. One such relationship is expressed as the voltage sensitivity, and an understanding of voltage sensitivity is very useful to describe DC distribution systems. In this paper, a formulation for a novel approximate expression for the voltage sensitivity in a radial DC distribution system is presented. The approximate expression is derived from the power flow equation with some additional assumptions. The results of approximate expression is compared with an exact calculation, and relations between the voltage sensitivity and electrical quantities are analyzed analytically using both the exact form and the approximate voltage sensitivity equation.
Full article

The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to

The carbon emissions trading market and direct power purchases by large consumers are two promising directions of power system development. To trace the carbon emission flow in the power grid, the theory of carbon emission flow is improved by allocating power loss to the load side. Based on the improved carbon emission flow theory, an optimal dispatch model is proposed to optimize the cost of both large consumers and the power grid, which will benefit from the carbon emissions trading market. Moreover, to better simulate reality, the direct purchase of power by large consumers is also considered in this paper. The OPF (optimal power flow) method is applied to solve the problem. To evaluate our proposed optimal dispatch strategy, an IEEE 30-bus system is used to test the performance. The effects of the price of carbon emissions and the price of electricity from normal generators and low-carbon generators with regards to the optimal dispatch are analyzed. The simulation results indicate that the proposed strategy can significantly reduce both the operation cost of the power grid and the power utilization cost of large consumers.
Full article

The concern of energy price hikes and the impact of climate change because of energy generation and usage forms the basis for residential building energy conservation. Existing energy meters do not provide much information about the energy usage of the individual appliance apart

The concern of energy price hikes and the impact of climate change because of energy generation and usage forms the basis for residential building energy conservation. Existing energy meters do not provide much information about the energy usage of the individual appliance apart from its power rating. The detection of the appliance energy usage will not only help in energy conservation, but also facilitate the demand response (DR) market participation as well as being one way of building energy conservation. However, energy usage by individual appliance is quite difficult to estimate. This paper proposes a novel approach: an unsupervised disaggregation method, which is a variant of the hidden Markov model (HMM), to detect an appliance and its operation state based on practicable measurable parameters from the household energy meter. Performing experiments in a practical environment validates our proposed method. Our results show that our model can provide appliance detection and power usage information in a non-intrusive manner, which is ideal for enabling power conservation efforts and participation in the demand response market.
Full article

We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically

We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically modeled to find the optimal operation conditions and illustrated with physical interpretation of how to achieve optimal energy management in the cooperative multi-microgrid community. This global electric energy optimization of the cooperative community is realized by the ancillary internal trading between the microgrids in the cooperative community which reduces the extra cost from unnecessary external trading by adjusting the electric energy production amounts of combined heat and power (CHP) generators and amounts of both internal and external electric energy trading of the cooperative community. A simulation study is also conducted to validate the proposed mathematical energy management models.
Full article

The conventional control paradigm for a heat pump with a less efficient auxiliary heating element is to keep its temperature set point constant during the day. This constant temperature set point ensures that the heat pump operates in its more efficient heat-pump mode

The conventional control paradigm for a heat pump with a less efficient auxiliary heating element is to keep its temperature set point constant during the day. This constant temperature set point ensures that the heat pump operates in its more efficient heat-pump mode and minimizes the risk of activating the less efficient auxiliary heating element. As an alternative to a constant set-point strategy, this paper proposes a learning agent for a thermostat with a set-back strategy. This set-back strategy relaxes the set-point temperature during convenient moments, e.g., when the occupants are not at home. Finding an optimal set-back strategy requires solving a sequential decision-making process under uncertainty, which presents two challenges. The first challenge is that for most residential buildings, a description of the thermal characteristics of the building is unavailable and challenging to obtain. The second challenge is that the relevant information on the state, i.e., the building envelope, cannot be measured by the learning agent. In order to overcome these two challenges, our paper proposes an auto-encoder coupled with a batch reinforcement learning technique. The proposed approach is validated for two building types with different thermal characteristics for heating in the winter and cooling in the summer. The simulation results indicate that the proposed learning agent can reduce the energy consumption by 4%–9% during 100 winter days and by 9%–11% during 80 summer days compared to the conventional constant set-point strategy.
Full article

A linear function submission-based double auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a

A linear function submission-based double auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP). This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor.
Full article

Taking advantage of two-way communication infrastructure and bidirectional energy trading between utility companies and customers in the future smart grid (SG), autonomous energy management programs become crucial to the demand-side management (DSM). Most of the existing autonomous energy management schemes are for the

Taking advantage of two-way communication infrastructure and bidirectional energy trading between utility companies and customers in the future smart grid (SG), autonomous energy management programs become crucial to the demand-side management (DSM). Most of the existing autonomous energy management schemes are for the scenario with a single utility company or the scenario with one-way energy trading. In this paper, an autonomous household energy management system with multiple utility companies and multiple residential customers is studied by considering the bidirectional energy trading. To minimize the overall costs of both the utility companies and the residential customers, the energy management system is formulated as a double cooperative game. That is, the interaction among the residential users is formulated as a cooperative game, where the players are the customers and the strategies are the daily schedules of their household appliances; and the interaction among the utility companies is also formulated as a cooperative game, where the players are the suppliers and the strategies are the proportions of the daily total energy they provide for the customers. Without loss of generality, the bidirectional energy trading in the double cooperative game is formulated by allowing plug-in electric vehicles (PEVs) to discharge and sell energy back. Two distributed algorithms will be provided to realize the global optimal performance in terms of minimizing the energy costs, which can be guaranteed at the Nash equilibriums of the formulated cooperative games. Finally, simulation results illustrated that the proposed double cooperative game can benefit both the utility companies and residential users significantly.
Full article

High-availability seamless redundancy (HSR) is a protocol for Ethernet networks that provides duplicated frames with zero recovery time in the event of any network component’s failure. It is suited for applications that demand high availability and a very short time-outs such as substation

High-availability seamless redundancy (HSR) is a protocol for Ethernet networks that provides duplicated frames with zero recovery time in the event of any network component’s failure. It is suited for applications that demand high availability and a very short time-outs such as substation automation systems (SAS). However, HSR generates excessive unnecessary unicast frames and spreads them throughout connected-ring networks, whether or not the destination node exists in network’s rings. This unnecessary redundant traffic causes high bandwidth consumption, resulting in degradation of network performance. In this paper, we introduce a novel approach for filtering and reducing HSR unicast traffic in connected-ring networks, called “filtering HSR traffic” (FHT). The purpose of FHT is to filter HSR unicast traffic and remove circulated traffic for all rings in connected-ring networks. Therefore, FHT significantly reduces network unicast traffic in connected-ring networks. The traffic performance of FHT has been analyzed, evaluated, and compared to that of standard HSR protocol and the port locking (PL) approach. Various simulations were conducted to validate the traffic performance analysis. Analytical and simulation results showed that, for our sample network, FHT reduced network unicast traffic by about 82% compared with standard HSR and by about 56% compared with the PL approach, thus freeing up network bandwidth and improving network traffic performance.
Full article

In this paper, a locational marginal pricing algorithm is proposed to control the voltage in unbalanced distribution grids. The increasing amount of photovoltaic (PV) generation installed in the grid may cause the voltage to rise to unacceptable levels during periods of low consumption.

In this paper, a locational marginal pricing algorithm is proposed to control the voltage in unbalanced distribution grids. The increasing amount of photovoltaic (PV) generation installed in the grid may cause the voltage to rise to unacceptable levels during periods of low consumption. With locational prices, the distribution system operator can steer the reactive power consumption and active power curtailment of PV panels to guarantee a safe network operation. Flexible loads also respond to these prices. A distributed gradient algorithm automatically defines the locational prices that avoid voltage problems. Using these locational prices results in a minimum cost for the distribution operator to control the voltage. Locational prices can differ between the three phases in unbalanced grids. This is caused by a higher consumption or production in one of the phases compared to the other phases and provides the opportunity for arbitrage, where power is transferred from a phase with a low price to a phase with a high price. The effect of arbitrage is analyzed. The proposed algorithm is applied to an existing three-phase four-wire radial grid. Several simulations with realistic data are performed.
Full article

With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly

With the development of modern society, the scale of the power system is rapidly increased accordingly, and the framework and mode of running of power systems are trending towards more complexity. It is nowadays much more important for the dispatchers to know exactly the state parameters of the power network through state estimation. This paper proposes a robust power system WLS state estimation method integrating a wide-area measurement system (WAMS) and SCADA technology, incorporating phasor measurements and the results of the traditional state estimator in a post-processing estimator, which greatly reduces the scale of the non-linear estimation problem as well as the number of iterations and the processing time per iteration. This paper firstly analyzes the wide-area state estimation model in detail, then according to the issue that least squares does not account for bad data and outliers, the paper proposes a robust weighted least squares (WLS) method that combines a robust estimation principle with least squares by equivalent weight. The performance assessment is discussed through setting up mathematical models of the distribution network. The effectiveness of the proposed method was proved to be accurate and reliable by simulations and experiments.
Full article

In this paper, a load adaptive control method to improve the efficiency and dynamic performance of the Phase-Shifted Full-Bridge (PSFB) converter which works under a wide range of load conditions is presented. The proposed control method can be used as a battery charger

In this paper, a load adaptive control method to improve the efficiency and dynamic performance of the Phase-Shifted Full-Bridge (PSFB) converter which works under a wide range of load conditions is presented. The proposed control method can be used as a battery charger since this application demands a wide range of load conditions. The composition of the PSFB converter’s losses and the loss analysis model are both discussed. According to this model, the optimum switching frequency which results in minimum power loss is adopted to improve the efficiency. The relationship between switching frequency and power loss is formulated over a wide load range. Indicated by this kind of relationship, the proposed controller adjusts the switching frequency at different load currents. Moreover, an adaptive gain adjustment controller is applied to replace the traditional controller, with the aim to improve the dynamic performance which is influenced by the changes of the switching frequency and load current. In addition, the experimental results show that the maximum improvement of efficiency is up to 20%. These results confirm the effectiveness of the proposed load adaptive control method.
Full article

Subsynchronous oscillation (SSO) of generators caused by high voltage direct current (HVDC) systems can be solved by applying supplemental subsynchronous damping controller (SSDC). SSDC application in mitigating SSO of single-generator systems has been studied intensively. This paper focuses on SSDC application in mitigating

Subsynchronous oscillation (SSO) of generators caused by high voltage direct current (HVDC) systems can be solved by applying supplemental subsynchronous damping controller (SSDC). SSDC application in mitigating SSO of single-generator systems has been studied intensively. This paper focuses on SSDC application in mitigating SSO of multi-generator systems. The phase relationship of the speed signals of the generators under their common mechanical natural frequencies is a key consideration in SSDC design. The paper studies in detail the phase relationship of the speed signals of two generators in parallel under their shared mechanical natural frequency, revealing regardless of whether the two generators are identical or not, there always exists a common-mode and an anti-mode under their common natural frequency, and the phase relationship of the speed signals of the generators depends on the extent to which the anti-mode is stimulated. The paper further demonstrates that to guarantee the effectiveness of SSDC, the anti-phase mode component of its input signal should be eliminated. Based on the above analysis, the paper introduces the design process of SSDC for multi-generator systems and verifies its effectiveness through simulation in Power Systems Computer Aided Design/Electromagnetic Transients including Direct Current (PSCAD/EMTDC).
Full article

The volatility of wind power poses great challenges to the operation of power systems. This paper deals with the economic dispatch problems presented by energy storage in wind integrated systems. A policy iteration algorithm for deriving the cost optimal policy of real-time scheduling

The volatility of wind power poses great challenges to the operation of power systems. This paper deals with the economic dispatch problems presented by energy storage in wind integrated systems. A policy iteration algorithm for deriving the cost optimal policy of real-time scheduling is proposed, taking the effect of wind forecast uncertainties into account. First, energy loss and use of fast-ramping generation are selected as the performance metrics. Then, a policy iteration algorithm is developed using the Perturbed Markov decision process. This algorithm has a two-level optimization structure in which both the long-term and short-term behaviors of real-time scheduling policy are optimized. In addition, a unified optimal storage control strategy is presented. The feasibility of the proposed methodology is demonstrated via the wind power archive of Electric Reliability Council of Texas (ERCOT). Through comparative numerical experiments, both the performance of the policy iteration algorithm in the short-term and long-term are verified and the consistency, robustness, good convergence and high computational efficiency of the proposed algorithm are also corroborated.
Full article

The variations in irradiance produced by changes in cloud cover can cause rapid fluctuations in the power generated by large photovoltaic (PV) plants. As the PV power share in the grid increases, such fluctuations may adversely affect power quality and reliability. Thus, energy

The variations in irradiance produced by changes in cloud cover can cause rapid fluctuations in the power generated by large photovoltaic (PV) plants. As the PV power share in the grid increases, such fluctuations may adversely affect power quality and reliability. Thus, energy storage systems (ESS) are necessary in order to smooth power fluctuations below the maximum allowable. This article first proposes a new control strategy (step-control), to improve the results in relation to two state-of-the-art strategies, ramp-rate control and moving average. It also presents a method to quantify the storage capacity requirements according to the three different smoothing strategies and for different PV plant sizes. Finally, simulations shows that, although the moving-average (MA) strategy requires the smallest capacity, it presents more losses (2–3 times more) and produces a much higher number of cycles over the ESS (around 10 times more), making it unsuitable with storage technologies as lithium-ion. The step-control shown as a better option in scenery with exigent ramp restrictions (around 2%/min) and distributed generation against the ramp-rate control in all ESS key aspects: 20% less of capacity, up to 30% less of losses and a 40% less of ageing. All the simulations were based on real PV production data, taken every 5 s in the course of one year (2012) from a number of systems with power outputs ranging from 550 kW to 40 MW.
Full article